- For (target customers)
- Who must (solve a specific problem)
- Our product is a new (new product category)
- That provides (key breakthrough benefit vs. current way of doing things – which solves dilemma)
- Unlike (competitor in new category)
- We have (whole product most relevant for you)
The current list contains 438 sessions. The list will be updated regularly, at least once a day during reinvent. Last update: 2018-12-02 06:58 +00:00
Title | Description | Video |
---|---|---|
[NEW LANUCH!] Building modern apps using Amazon DynamoDB transactions (DAT374) | DynamoDB transactions enables developers to maintain correctness of their data at scale by adding atomicity and isolation guarantees for multi-item conditional ... | |
[NEW LAUNCH!] AWS License Manager Deep Dive (CMP393) | AWS License Manager is a new service that makes it easy to bring your existing licenses to the AWS cloud and reduce licensing costs. This service offers a ... | [ |
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't really have SREs and they make engineers pretty much do everything,
A guide for reviewing code and having your code reviewed.
Peer code reviews are the single biggest thing you can do to improve your code - Jeff Atwood
Code review is an important part of a team's development process. It helps to:
- disseminate knowledge about the codebase/technology/techniques across teams
- increase awareness of the features being developed
# MIT License | |
# Copyright (c) 2016 Chandler Abraham | |
# Permission is hereby granted, free of charge, to any person obtaining a copy | |
# of this software and associated documentation files (the "Software"), to deal | |
# in the Software without restriction, including without limitation the rights | |
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
# copies of the Software, and to permit persons to whom the Software is | |
# furnished to do so, subject to the following conditions: |
Update-ExecutionPolicy Unrestricted -Force | |
# Base | |
cinst BoxStarter.Chocolatey | |
cinst BoxStarter.WinConfig | |
# Chocolatey | |
cinst ChocolateyPackageUpdater | |
# Windows 8.1 Settings and Options |
a4b.amazonaws.com | |
acm-pca.amazonaws.com | |
acm.amazonaws.com | |
alexa-appkit.amazon.com | |
alexa-connectedhome.amazon.com | |
amazonmq.amazonaws.com | |
apigateway.amazonaws.com | |
application-autoscaling.amazonaws.com | |
appstream.application-autoscaling.amazonaws.com | |
appsync.amazonaws.com |
Availability Availability is the proportion of time that the system is functional and working. It is usually measured as a percentage of uptime. Application errors, infrastructure problems, and system load can all reduce availability.
A cloud application should have a service level objective (SLO) that clearly defines the expected availability, and how the availability is measured. When defining availability, look at the critical path. The web front-end might be able to service client requests, but if every transaction fails because it can't connect to the database, the application is not available to users.
Availability is often described in terms of "9s" — for example, "four 9s" means 99.99% uptime. The following table shows the potential cumulative downtime at different availability levels.
99% 1.68 hours 7.2 hours 3.65 days
# 1. export bookmarks | |
# 2. awk -f cbdd.awk bookmarks_12_4_16.html > uniq.html | |
# 3. import uniq.html | |
BEGIN { FS = " " } | |
$2 ~ /^HREF/ { | |
if (!($2 in seen)) { | |
seen[$2] | |
print $0 |